Great improvements continue to be made in conventional signal processing-based image compression techniques. Mainstream coding schemata use the statistical redundancy among pixels in pursuit of high coding efficiency. Current state-of-the-art JPEG2000 and MPEG-4 AVC/H.264 are two examples that greatly outperform the coding efficiency of previous generations. Perceptual quality, however, is largely ignored during conventional algorithm design. In addition, current developments also demonstrate that even small improvements are commonly accomplished at the expense of multiplying encoding complexity.
Recently, vision-related technologies have shown remarkable progress in interpretively synthesizing certain visual aspects of an image in order to provide good perceptual quality—instead of straining to achieve perfection of pixel-wise fidelity during generation of the image. For example, when presented with a small sample image of a texture, synthesis techniques are able to produce a large image that possesses perceptually similar texture.
To further enhance image compression techniques, what is needed is a way to combine artificial synthesis of some parts of an image with conventional coding principles in order to achieve improved image compression ratios and higher coding efficiency.